The impact of machine learning on patient care: A systematic review.

Artificial Intelligence in Medicine
David Ben-IsraelDavid W Cadotte

Abstract

Despite the expanding use of machine learning (ML) in fields such as finance and marketing, its application in the daily practice of clinical medicine is almost non-existent. In this systematic review, we describe the various areas within clinical medicine that have applied the use of ML to improve patient care. A systematic review was performed in accordance with the PRISMA guidelines using Medline(R), EBM Reviews, Embase, Psych Info, and Cochrane Databases, focusing on human studies that used ML to directly address a clinical problem. Included studies were published from January 1, 2000 to May 1, 2018 and provided metrics on the performance of the utilized ML tool. A total of 1909 unique publications were reviewed, with 378 retrospective articles and 8 prospective articles meeting inclusion criteria. Retrospective publications were found to be increasing in frequency, with 61 % of articles published within the last 4 years. Prospective articles comprised only 2 % of the articles meeting our inclusion criteria. These studies utilized a prospective cohort design with an average sample size of 531. The majority of literature describing the use of ML in clinical medicine is retrospective in nature and often outlines proof-of-conc...Continue Reading

Citations

Mar 1, 2020·Journal of Magnetic Resonance Imaging : JMRI·Albert de Roos, Qian Tao
Feb 9, 2021·Expert Review of Pharmacoeconomics & Outcomes Research·Pooyeh GrailiMary Argent-Katwala
Feb 14, 2021·Journal of Biomedical Informatics·Jiebin ChuZhengxing Huang
Oct 28, 2020·Materials Chemistry and Physics·Bankole I OladapoMohsen Zahedi
Jun 5, 2021·Chemical Communications : Chem Comm·Sophia ShenJun Chen
Jul 2, 2021·Advanced Science·Loïc LannelongueMichael Inouye

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